• Smart Structures and Systems
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• v.13 no.3
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• pp.453-471
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• 2014

The fault diagnosis of rolling element bearings has drawn considerable research attention in recent years because these fundamental elements frequently suffer failures that could result in unexpected machine breakdowns. Artificial intelligence algorithms such as artificial neural networks (ANNs) and support vector machines (SVMs) have been widely investigated to identify various faults. However, as the useful life of a bearing deteriorates, identifying early bearing faults and evaluating their sizes of development are necessary for timely maintenance actions to prevent accidents. This study proposes a new two-layer structure consisting of support vector regression machines (SVRMs) to recognize bearing fault patterns and track the fault sizes. The statistical parameters used to track the fault evolutions are first extracted to condense original vibration signals into a few compact features. The extracted features are then used to train the proposed two-layer SVRMs structure. Once these parameters of the proposed two-layer SVRMs structure are determined, the features extracted from other vibration signals can be used to predict the unknown bearing health conditions. The effectiveness of the proposed method is validated by experimental datasets collected from a test rig. The results demonstrate that the proposed method is highly accurate in differentiating between fault patterns and determining their fault severities. Further, comparisons are performed to show that the proposed method is better than some existing methods.

• Wind and Structures
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• v.21 no.6
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• pp.693-707
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• 2015

The efficiency of wind turbines (WT) is primarily reflected in their ability to generate electricity at any time. Downtimes of WTs due to "conventional" inspections are cost-intensive and undesirable for investors. For this reason, there is a need for structural health monitoring (SHM) systems, to enable service and maintenance on demand and to increase the inspection intervals. In general, monitoring increases the cost effectiveness of WTs. This publication concentrates on the application of two vibration-based SHM algorithms for stability and structural change monitoring of offshore WTs. Only data driven, output-only algorithms based on stochastic subspace identification (SSI) in time domain are considered. The centerpiece of this paper deals with the rough mathematical description of the dynamic behavior of offshore WTs and with the basic presentation of stochastic subspace-based algorithms and their application to these structures. Due to the early stage of the industrial application of SHM on offshore WT on the one side and the required confidentiality to the plant manufacturer and operator on the other side, up to now it is not possible to analyze different isolated structural damages resp. changes in a systematic manner, directly by means of in-situ measurement and to make these "acknowledgements" publicly available. For this reason, the sensitivity of the methods for monitoring purposes are demonstrated through their application on long time measurements from a 1:10 large scale test rig of an offshore WT under different conditions: undamaged, different levels of loosened bolt connections between tower parts, different levels of fouling, scouring and structure inclination. The limitation and further requirements for the approaches and their applicability on real foundations are discussed along the paper.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.7
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• pp.773-778
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• 2011

Accelerometers are widely used to measure the lateral vibrations of pipe-like structures such as a gun tube under impulse loads. Stress waves that precede the lateral vibrations due to the explosion within a gun contribute little to the vibrations, but saturate the accelerometer input. A mechanical filter eliminates this high-frequency stress wave and only transmits the signal corresponding to the lateral vibrations. The mechanical filter consists of a mechanical structure for mounting the accelerometers and a damping material. The low-pass filter characteristics are determined from the equivalent damping and stiffness property of this damping material. In this paper, we tested nine commercially available damping materials for their vibration characteristics by using a test rig. We also observed the change in the vibration characteristics while compressing the material. We designed and manufactured a mechanical filter and verified its filtering performance.

• Journal of Advanced Marine Engineering and Technology
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• v.31 no.1
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• pp.26-33
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• 2007

The intake swirl motion, as one of dominant effects for an engine combustion. is very effective for turbulence enhancement during the compression process in the cylinder of 2-valve engine. Because the combustion flame speed is determined by the turbulence that is mainly generated from the mean flow of the charge air motion in intake port system. This paper describes the experimental results of swirl flow and combustion characteristics by using the oil spot method and back-scattering Laser Doppler velocimeter (LDV) in 2-valve single cylinder transparent LPG engine using the liquid phase LPG injection. For this. various intake port configurations were developed by using the flow box system and swirl ratios for different intake port configurations were determined by impulse swirl meter in a steady flow rig test. And the effects of intake swirl ratio on combustion characteristics in an LPG engine were analyzed with some analysis parameters that is swirl ratio. mean flow coefficient, swirl mean velocity fuel conversion efficiency. combustion duration and cyclic variations of indicated mean effective pressure(IMEP). As these research results, we found that the intake port configuration with swirl ratio of 2.0 that has a reasonable lean combustion stability is very suitable to an $11{\ell}$ heavy-duty LPG engine with liquid phase fuel injection system. It also has a better mean flow coefficient of 0.34 to develope a stable flame kernel and to produce high performance. This research expects to clarify major factor that effects on the design of intake port efficiently with the optimized swirl ratio for the heavy duty LPG engine.

• Journal of the Earthquake Engineering Society of Korea
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• v.7 no.3
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• pp.17-22
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• 2003

This paper presents an experimental investigation of a reversible colloidal seismic damper, which is statically loaded, The porous matrix is composed from silica gel (labyrinth or central-cavity architecture), coated by organo-silicones substances, in order to achieve a hydrophobic surface. Water is considered as associated lyophobic liquid. Reversible colloidal damper static test rig and the measuring technique of the static hysteresis are described. Influence of the pare and particle diameters, particle architecture and length of the grafted molecule upon the reversible colloidal damper hysteresis is investigated, for distinctive types and mixtures of porous matrices, Variation of the reversible colloidal damper dissipated energy and efficiency with temperature, pressure, is illustrated.

• Advances in aircraft and spacecraft science
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• v.6 no.6
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• pp.529-550
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• 2019

The effect of multiple process parameters on a set of continuous response variables is, especially in experimental designs, difficult and intricate to determine. Due to the complexity in aeroacoustic and vibroacoustic studies, the often-performed simple one-factor-at-a-time method turns out to be the least effective approach. In contrast, the statistical Design of Experiments is a technique used with the objective to maximize the obtained information while keeping the experimental effort at a minimum. The presented work aims at giving insights on Design of Experiments applied to aeroacoustic and vibroacoustic problems while comparing different experimental designs and approximation models. For this purpose, an experimental rig of a ducted low-pressure fan is developed that allows gathering data of both, aerodynamic and aeroacoustic nature while analysing three independent process parameters. The experimental designs used to sample the design space are a Central Composite design and a Box-Behnken design, both used to model a response surface regression, and Latin Hypercube sampling to model an Artificial Neural network. The results indicate that Latin Hypercube sampling extracts information that is more diverse and, in combination with an Artificial Neural network, outperforms the quadratic response surface regressions. It is shown that the Latin Hypercube sampling, initially developed for computer-aided experiments, can also be used as an experimental design. To further increase the benefit of the presented approach, spectral information of every experimental test point is extracted and Artificial Neural networks are chosen for modelling the spectral information since they show to be the most universal approximators.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.2
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• pp.166-174
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• 2014

Fuel injection pressure has steadily increased in diesel engines for the purpose of improving fuel efficiency and cleaning exhaust gas, but it has now reached a point, where the cost for higher pressure does not warrant additional gains. Common rail systems on modern diesel engines have fuel pumps that are mechanically driven by crankshaft. The pumps actually house two pumping module inside: a low pressure pump component and a high pressure pump component. Part of the fuel compressed by the low pressure component returns to the tank in the process of maintaining the pressure in the common rail. Since the returning fuel represents pumping loss, fuel economy improves if the returned fuel can be eliminated by using a properly controled electrical fuel pump. As the first step in developing an electrical fuel pump the fuel supply system on a 6 liter diesel engine was modeled with AMESim to analyze the workload and the fuel feed rate of the injection pump, and the results served as basis for selecting a suitable servo motor and a reducer to drive the pump. A motor controller was built using a DSP and a program which controls the common rail pressure using a proportional control method based on the target fuel pressure information from the engine ECU. A test rig to evaluate performance of the fuel pump is implemented and used to show that the newly developed electrically driven fuel pump can satisfy the fuel flow demand of the engine under various operating conditions when the rotational speed of the pump is adequately controlled.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.37 no.6
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• pp.551-558
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• 2013

A support vector machine (SVM) is a very powerful classification algorithm when a set of training data, each marked as belonging to one of several categories, is given. Therefore, SVM techniques have been used as one of the diagnostic tools in machine learning as well as in pattern recognition. In this paper, we present the results of classifying ball bearing fault types and severities using SVM with an optimized feature set based on the minimum distance rule. A feature set as an input for SVM includes twelve time-domain and nine frequency-domain features that are extracted from the measured vibration signals and their decomposed details and approximations with discrete wavelet transform. The vibration signals were obtained from a test rig to simulate various bearing fault conditions.

• Transactions of the Korean Society of Automotive Engineers
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• v.17 no.1
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• pp.43-49
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• 2009

A catalyzed diesel particulate filter (CDPF) causes the progressive increase in back pressure of an exhaust system due to the loading of soot particles. To minimize pressure drop which is generated by CDPF, the filter should be regenerated when it collects a certain quantity of soot. It is important to know characteristics of regeneration of CDPF with various of exhaust gas temperatures and compositions. The oxidation of HC in DOC leads to increase gas temperature of DOC downstream. The increased gas temperature by DOC has an positive effect on CDPF regeneration. This study presents characteristics of regeneration of CDPF with DOC according to various gas composition, such as HC and $O_2$ concentration. The test-rig is used to control each gas composition and temperature during regeneration of CDPF. Experimental results indicate that the increased concentration of $O_2$ regenerates DPF more actively. With increasing HC concentration, the gas temperature of CDPF upstream increased due to more oxidation of HC. But excessive supply of HC leads to decrease of $O_2$ concentration in the CDPF, which makes it hard to regenerate CDPF.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.3
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• pp.103-111
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• 2006

The spray behavior of direct-injection spark-ignition(DISI) engines is crucial for obtaining the required mixture distribution for optimal engine combustion. The spray characteristics of DISI engines are affected by many factors such as piston bowl shape, air flow, ambient temperature, injection pressure and fuel temperature. In this study, the effect of fuel temperature on the spray and combustion characteristics was partially investigated for the wall-guided system. The effect of fuel temperature on the fan spray characteristics was investigated in a steady flow rig embodied in a wind tunnel. The shadowgraphy and direct imaging methods were employed to visualize the spray development at different fuel temperatures. The microscopic characteristics of spray were investigated by the particle size measurements using a phase Doppler anemometry(PDA). The effect of injector temperature on the engine combustion characteristics during cold start and warming-up operating conditions was also investigated. Optical single cylinder DISI engine was used for the test, and the successive flame images captured by high speed camera, engine-out emissions and performance data have been analyzed. This could give the way of forming the stable mixture near the spark plug to achieve the stable combustion of DISI engine.